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Powerfully Simple Trade Promotion Optimization

Promotions, advertising and other forms of “demand shaping” can be enormously expensive, costing more than 15% of gross revenues. Yet determining their actual impact or “lift” remains a daunting problem. A large number of variables with complex interactions are buried in huge amounts of data with a high degree of noise. Even with substantial expertise and fairly consistent baseline demand, it’s usually not possible to understand correlations among variables.

To solve this problem, we turned to a powerful machine learning technology called Rulex®. This technique recognizes the shared characteristics of promotional events and identifies their effect on normal sales. It extracts knowledge about which variables most impact demand and produces a set of simple intelligible rules, easily understood by the user. Fast multi-dimensional modelling handles both qualitative and quantitative variables. It can also handle unstructured or partial data.

Our customers are deploying machine learning-based analytics for applications such as:

  • Media events forecasting, to optimize spend and reduce lost sales and stock-outs
  • Promotion and social media optimization, to identify the promotions that consumers want and maximize margin return on marketing spend
  • Leveraging web data (such as page views and bounce rates) to predict which new product introductions will become ‘the stars’
  • Customer segmentation clustering to understand the complex behavioural patterns of each customer segment

This breakthrough technique creates a major improvement in demand visibility, forecast quality and level of demand modeling.

View Infographic See how Danone increased their forecast accuracy to 92%
Read Brief Learn about improved promotion effectiveness at the Product-Channel level
Read Case Study Learn how Granarolo achieved 95% service levels through imprived promotion forecasting


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